[PDF] Top 20 Maximum-Likelihood Estimation of Admixture Proportions From Genetic Data
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Maximum-Likelihood Estimation of Admixture Proportions From Genetic Data
... The likelihood method therefore does not require that and Excoffier (1998) and Dupanloup and Bertor- each sample must be taken from the hybrid population elle (2001) as BD (their m R estimator), and that of ... See full document
20
Inferring Population Structure and Admixture Proportions in Low-Depth NGS Data
... and admixture proportions in low-depth next-generation sequencing (NGS) ...of genetic data but are associated with statistical uncertainty, especially for low-depth sequencing ... See full document
13
Estimating Individual Admixture Proportions from Next Generation Sequencing Data
... obtain genetic data for all accessible genetic variations in the ...for admixture analysis rely on known ...inferred from low-depth sequencing data without introducing ... See full document
33
Maximum likelihood estimation of reviewers' acumen in central review setting: categorical data
... incomplete data likelihood function, equation 4, is a mixture of multinomial probabilities, in which the mixture probabilities, γ jl k , are ...incomplete-data likelihood function directly is ... See full document
10
Maximum-Likelihood Estimation of Relatedness
... marker data to quantify ...traditional maximum-likelihood estimator in relation to the ...traditional maximum-likelihood estimator exhibits a lower standard error under essentially all ... See full document
16
Joint Maximum Likelihood Channel Estimation and Data Detection for MIMO Systems
... the data length N ...the genetic algorithm (GA) and the RWBS algorithm were used to find the ML channel and data estimation for single-input multiple-output systems, and it was seen that the ... See full document
5
Blind Joint Maximum Likelihood Channel Estimation and Data Detection for SIMO Systems
... decodes data based on the given channel model and feeds back the corresponding likelihood metric to the RWBS ...a genetic algorithm (GA) can be used in place of the RWBS algorithm to optimise the ... See full document
5
Approximate maximum likelihood estimation for population genetic inference
... approximate maximum likelihood estimate is obtained using a stochastic version of the Nelder-Mead ...simulated maximum indirect likelihood (SMIL) estimator that is also based on approximations ... See full document
22
Estimation of Admixture Proportions: A Likelihood-Based Approach Using Markov Chain Monte Carlo
... tified. We suggested in the analysis of the Jamaican data ments that greatly helped us improve the article. We are also grateful set that the robustness of admixture estimates should to E. Parra and M. ... See full document
16
Maximum likelihood joint channel and data estimation using genetic algorithms
... suffers from the drawback of slow ...received data samples and extensive computation to estimate higher order ...the maximum likelihood sequence estimation (MLSE) to perform a joint ... See full document
5
Unit Root Tests in Panel Data: Weighted Symmetric Estimation and Maximum Likelihood Estimation
... countries from 1970 to 1998. These historical data are available from the website of the United States Department of Labor ...GDP data are constructed using Elteto-K¨ oves-Szulc (EKS) ... See full document
103
Maximum Likelihood Estimation of Feature Based Distributions
... ML estimation of the probability of T (q, σ) is obtained by dividing the number of times this transition is used in parsing the sample S by the number of times state q is encountered in the pars- ing of S ...ML ... See full document
10
Estimation of the Reliability Measures of a Three component System with Human Errors and Common Cause Failures
... Therefore, the M L estimators are generally hard to beat consistently, even in small samples and our simulation results showed a strong preference for the M L estimation method for situations arising in practical ... See full document
7
A simple approach to maximum intractable likelihood estimation
... conducting maximum likelihood estimation via simulation in settings in which the likelihood cannot (readily) be evaluated and provides theoretical and empirical support for that ...a ... See full document
24
fastSTRUCTURE: Variational Inference of Population Structure in Large SNP Data Sets
... violations from HWE, we selected three population groups that have relatively little population structure (East Asia, Europe, Bantu Africa), constructed three large groups of individuals from these ... See full document
21
Maximum Entropy and Maximum Likelihood Estimation for the Three Parameter Kappa Distribution
... (3) for a continuous non-negative random variable X, where f x is the probability density function of X. The given information used in the principle of maximum entropy (ME) is expressed as a set of ... See full document
5
A maximum likelihood method for estimating genome length using genetic linkage data.
... We propose a maximum likelihood method for estimating this quantity from counts of recombinants and nonrecombinants between marker locus pairs studied from a backcross [r] ... See full document
8
THE APPLICATION OF THE "METHOD OF MAXIMUM LIKELIHOOD" TO THE ESTIMATION OF LINKAGE
... F1cmv3.-A factor linked to one of two duplicate factors: Amount of information concerning linkage supplied per plant by a backcross to a triple recessive, and by an Fz, using ([r] ... See full document
19
On the Approximate Maximum Likelihood Estimation for Diffusion Processes
... We report results from simulation studies which are designed to confirm the theoretical findings on the AMLE as reported in the earlier sections. To allow verification with the full MLE, we considered the Vasicek ... See full document
39
Maximum likelihood estimation of variance components
... The other diagnostic plots given in Figure 7.5 - Figure 7.7 confirm that the data set no longer contains serious outliers. There is still some curvature in the matrix of Q-Q plots (Figure 7.5), especially in the ... See full document
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